T2 relaxation time mapping reveals age- and species-related diversity of collagen network architecture in articular cartilage

SummaryObjectiveThe magnetic resonance imaging (MRI) parameter T2 relaxation time has been shown to be sensitive to the collagen network architecture of articular cartilage. The aim of the study was to investigate the agreement of T2 relaxation time mapping and polarized light microscopy (PLM) for the determination of histological properties (i.e., zone and fibril organization) of articular cartilage.MethodsT2 relaxation time was determined at 9.4T field strength in healthy adult human, juvenile bovine and juvenile porcine patellar cartilage, and related to collagen anisotropy and fibril angle as measured by quantitative PLM.ResultsBoth T2 and PLM revealed a mutually consistent but varying number of collagen-associated laminae (3, 3–5 or 3–7 laminae in human, porcine and bovine cartilage, respectively). Up to 44% of the depth-wise variation in T2 was accounted for by the changing anisotropy of collagen fibrils, confirming that T2 contrast of articular cartilage is strongly affected by the collagen fibril anisotropy. A good correspondence was observed between the thickness of T2-laminae and collagenous zones as determined from PLM anisotropy measurements (r=0.91, r=0.95 and r=0.91 for human, bovine and porcine specimens, respectively).ConclusionsAccording to the present results, T2 mapping is capable of detecting histological differences in cartilage collagen architecture among species, likely to be strongly related to the differences in maturation of the tissue. This diversity in the MRI appearance of healthy articular cartilage should also be recognized when using juvenile animal tissue as a model for mature human cartilage in experimental studies

Iterative and discrete reconstruction in the evaluation of the rabbit model of osteoarthritis

Micro-computed tomography (µCT) is a standard method for bone morphometric evaluation. However, the scan time can be long and the radiation dose during the scan may have adverse effects on test subjects, therefore both of them should be minimized. This could be achieved by applying iterative reconstruction (IR) on sparse projection data, as IR is capable of producing reconstructions of sufficient image quality with less projection data than the traditional algorithm requires. In this work, the performance of three IR algorithms was assessed for quantitative bone imaging from low-resolution data in the evaluation of the rabbit model of osteoarthritis. Subchondral bone images were reconstructed with a conjugate gradient least squares algorithm, a total variation regularization scheme, and a discrete algebraic reconstruction technique to obtain quantitative bone morphometry, and the results obtained in this manner were compared with those obtained from the reference reconstruction. Our approaches were sufficient to identify changes in bone structure in early osteoarthritis, and these changes were preserved even when minimal data were provided for the reconstruction. Thus, our results suggest that IR algorithms give reliable performance with sparse projection data, thereby recommending them for use in µCT studies where time and radiation exposure are preferably minimized. © 2018, The Author(s).Peer reviewe

Defective WNT signaling may protect from articular cartilage deterioration - a quantitative MRI study on subjects with a heterozygous WNT1 mutation

Objective: WNT signaling is of key importance in chondrogenesis and defective WNT signaling may contribute to the pathogenesis of osteoarthritis and other cartilage diseases. Biochemical composition of articular cartilage in patients with aberrant WNT signaling has not been studied. Our objective was to assess the knee articular cartilage in WNT1 mutation-positive individuals using a 3.0T MRI unit to measure cartilage thickness, relaxation times, and texture features. Design: Cohort comprised mutation-positive (N = 13; age 17-76 years) and mutation-negative (N = 13; 16-77 years) subjects from two Finnish families with autosomal dominant WNT1 osteoporosis due to a heterozygous missense mutation c.652T>G (p.C218G) in WNT1. All subjects were imaged with a 3.0T MRI unit and assessed for cartilage thickness, T2 and T1 rho relaxation times, and T2 texture features contrast, dissimilarity and homogeneity of T2 relaxation time maps in six regions of interest (ROIs) in the tibiofemoral cartilage. Results: All three texture features showed opposing trends with age between the groups in the medial tibiofemoral cartilage (P = 0.020-0.085 for the difference of the regression coefficients), the mutation-positive individuals showing signs of cartilage preservation. No significant differences were observed in the lateral tibiofemoral cartilage. Cartilage thickness and means of T2 relaxation time did not differ between groups. Means of T1r relaxation time were significantly different in one ROI but the regression analysis displayed no differences. Conclusions: Our results show less age-related cartilage deterioration in the WNT1 mutation-positive than the mutation-negative subjects. This suggests, that the WNT1 mutation may alter cartilage turnover and even have a potential cartilage-preserving effect. (C) 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.Peer reviewe

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning:data from the Multicenter Osteoarthritis Study (MOST)

Abstract Objective: To assess the ability of imaging-based deep learning to detect radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs. Design: Knee lateral view radiographs were extracted from The Multicenter Osteoarthritis Study (MOST) public use datasets (n = 18,436 knees). Patellar region-of-interest (ROI) was first automatically detected, and subsequently, end-to-end deep convolutional neural networks (CNNs) were trained and validated to detect the status of patellofemoral OA. Patellar ROI was detected using deep-learning-based object detection method. Atlas-guided visual assessment of PFOA status by expert readers provided in the MOST public use datasets was used as a classification outcome for the models. Performance of classification models was assessed using the area under the receiver operating characteristic curve (ROC AUC) and the average precision (AP) obtained from the Precision-Recall (PR) curve in the stratified 5-fold cross validation setting. Results: Of the 18,436 knees, 3,425 (19%) had PFOA. AUC and AP for the reference model including age, sex, body mass index (BMI), the total Western Ontario and McMaster Universities Arthritis Index (WOMAC) score, and tibiofemoral Kellgren–Lawrence (KL) grade to detect PFOA were 0.806 and 0.478, respectively. The CNN model that used only image data significantly improved the classifier performance (ROC AUC = 0.958, AP = 0.862). Conclusion: We present the first machine learning based automatic PFOA detection method. Furthermore, our deep learning based model trained on patella region from knee lateral view radiographs performs better at detecting PFOA than models based on patient characteristics and clinical assessments

Patients', radiographers' and radiography students’ experiences of 360° virtual counselling environment for the coronary computed tomography angiography: A qualitative study

Abstract Introduction The aim of this study was to describe patients', radiographers' and radiography students’ experiences of the developed 360° virtual counselling environment (360°VCE) for the coronary computed tomography angiography (cCTA). Methods A descriptive qualitative approach was used. The participants were cCTA patients (n = 10), radiographers (n = 10) and radiography students (n = 10) who used the 360°VCE and visited or worked at a university hospital in Finland. The 360°VCE, resembling the authentic environments of a CT imaging unit, included digital counselling materials in text, image, animation and video formats. Data were gathered through thematic interviews individually to obtain an understanding of participants’ perspectives and analyzed by inductive content analysis. Results Five main categories and 15 categories were identified. Identified benefits of the 360°VCE for patients included improvements in knowledge, spatial and environmental orientation, and senses of security and self-efficacy, with reductions in fear and nervousness. Patients found the counselling materials engaging, and that the 360° technology conveniently provided reassuring familiarity with the environment before their visit. Identified benefits for radiographers and radiography students included improvements in patients' mental preparedness, knowledge, spatial and environmental orientation, and reductions in patients’ fear, which eased procedures and enhanced diagnostic success. The 360°VCE also provided useful information and familiarization with the cCTA unit for students during clinical practice and staff of referring units.  Conclusion It seems that patients', radiographers' and radiography students' experiences of 360°VCE respond to patients’ needs by improved knowledge and reduced fears. Thus, current counselling practices can be usefully complemented with spherical panoramic imaging technology and online information delivery. Implications for practice The results may be used to improve patient counselling and care, thereby optimizing the cCTA examination procedure and reducing fear. However, further research is needed to characterize experiences of the 360° VCE more comprehensively. Keywords Counselling, Patient, Computed tomography, Radiographer, Digital, Virtua